Download Metabolism in the pre-implantation oocyte and embryo

Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Metabolism in the pre-implantation oocyte and embryo
M.L. Sutton-McDowall1, J.G. Thompson
Australian Research Council Centre of Excellence for Nanoscale BioPhotonics (CNBP), Robinson Research Institute, School of
Paediatrics and Reproductive Health and Institute for Photonics and Advanced Sensing, The University of Adelaide, Medical
School, Adelaide, SA, Australia.
Abstract
An understanding of oocyte and embryo
metabolism is critical to understanding and developing
in vitro culture systems. In the last 60-70 years there has
been a constant evolution in the way metabolism studies
have been conducted. This includes a change from
studying the metabolism of the oocyte alone vs. as a
whole cumulus oocyte complex. The study of in vivo
environments has lead to the creation of defined
sequential culture systems, resulting in overcoming
developmental blocks and improved embryo
development. And techniques for studying metabolism
have evolved from the use of radiolabelled isotopes to
increasingly specific fluorescence probes and
metabolomics, allowing for large, integrative profiles.
Metabolism is a potential diagnostic for selecting the
most likely embryos to implant. We envisage the future
of metabolism will involve the ability to measure ‘morein-less’ (more substrates, less volumes) and allow for a
holistic approach to understanding the relationship
between metabolism and developmental competence, as
it is unconceivable that a single metabolic output will be
able to assess health and/or quality.
embryo, in vitro embryo production,
Keywords:
metabolism, oocyte.
Introduction
Fifty years ago Robert Edwards discovered that
mechanical release of an oocyte from the ovarian antral
follicle could initiate the final stages of oocyte
maturation (Edwards, 1965). Since then, in vitro oocyte
maturation (IVM), in vitro fertilisation (IVF) and
culture of embryos post-fertilisation (in vitro embryo
culture, IVC); collectively known as in vitro embryo
production (IVP), has been widely utilised for the study
of pre-implantation oocyte and embryo development
and is increasingly utilised in livestock animal
production and human assisted reproduction.
An understanding of the metabolism of
cumulus oocyte complexes (COCs) and embryos is
critical, not only to enable the creation of improved
culture systems, resulting in the development of
healthier in vitro produced embryos, but metabolism is a
potential marker of developmental competence,
______________________________________________
1
Corresponding author: [email protected]
Phone: +61(8) 8313-1013
Received: May 20, 2015
Accepted: July 22, 2015
determining which embryos are the healthiest and
thereby have the highest chance of implantation and a
healthy pregnancy.
There are numerous excellent review articles
covering metabolism of the COC (Sutton et al., 2003b;
Thompson et al., 2007, 2014; Sutton-McDowall et al.,
2010; Krisher, 2013) and the embryo (Bavister, 1995;
Thompson, 2000; Leese et al., 2008; Leese, 2012). With
this in mind, the focus of this review is to present a brief
synopsis of changes in pre-implantation metabolism
through development, limitations to the current
metabolic diagnostics used and possible future
directions for determining metabolism of COCs and
pre-implantation embryos. Furthermore, while we
acknowledge that the COC and embryo utilise many
energy sources such as lipids (Sturmey et al., 2009;
Dunning et al., 2014) and amino acids (Wale and
Gardner, 2012), this review will focus on the
metabolism of carbohydrates and downstream signalling
molecules.
Metabolism: timing (and stage) is everything
The peri-conception period, covering the final
stages of oocyte maturation through to pre-implantation
embryo development, is a highly dynamic period, with
the COC and pre-implantation embryo exposed to
several different micro-environments, ranging from the
highly vascular, hence highly perfused ovarian follicle
to the low oxygen levels (Tervit et al., 1972; Maas et
al., 1976; Fischer and Bavister, 1993) and more mucus
environment of the uterus. It is well established that the
metabolism of the COC and pre-implantation embryo
varies (Fig. 1) and this is largely reflective of the in vivo
environment (Krisher, 2013).
In an attempt to improve IVP success, culture
systems have been formulated based on the composition
of the in vivo environment (reviewed by Summers and
Biggers, 2003; Sutton et al., 2003a; Table 1), resulting
in significantly higher rates of developmental
competence and pregnancy success rates. Indeed,
pioneering work by Tervit and colleagues used the
composition of sheep oviductal fluid (characterised by
Restall and Wales, 1966) to create synthetic oviductal
fluid (SOF) and performed culture in low oxygen
concentrations (Tervit et al., 1972), a system that is still
widely utilised, with modified versions used throughout
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
IVP in larger animals (Gandhi et al., 2000).
However, due to the static, yet highly
chemically defined nature of culture systems, vs. the
highly perfused and complex environments in vivo,
there is room for improvement and consequently the
compositions of IVP media suites are constantly
evolving. To date, the most successful media suites
include sequential media to accommodate changing
metabolic needs (Summers and Biggers, 2003; Lane and
Gardner, 2007), although this is challenged within the
human IVF field, suggesting that single media systems
are suitable (Cohen et al., 2008; Paternot et al., 2010).
Figure 1. Changes in the metabolism of cumulus oocyte complexes (COCs) and preimplantation embryos. 2PN = 2
pronuclei; GJC = gap junction communication; GV = germinal vesicle; HBP = hexosamine biosynthetic pathway;
ICM = inner cell mass; OxPhos = oxidative phosphorylation and TCA cycle = tricarboxylic acid cycle.
Table 1. Carbohydrate composition of the in vivo vs. in vitro environments that cumulus oocyte complexes (COCs)
and embryos are exposed to.
In vivo
Glucose
(mM)
1.4-2.31
2-3.8 2
Lactate
(mM)
3-6.41
5-14.42
Pyruvate
(mM)
0.4 1
COC
In vitro
1.5 (SOFM)
5.6 (M199)
0.33 (SOFM)
0.2 (M199)
Fertilisation
In vivo
In vitro
(Oviduct)
In vivo
(Uterus)
Embryo
In vitro
In vitro
(Cleavage)
(Post-Compaction)
2.4-33
0.5-3.114
2.8 (HTF)
0 (Fert TALP)
0.55
0.02-0.046
3.15 4
1.5
(SOFC1)
0.5 (G1.2)
3 (SOFC2)
3.2 (G2.2)
2.57
4.9-10.54
21.4 (HTF)
10 (Fert TALP)
8.65
5.94
10.5 (G1.2)
5.9 (G2.2)
0.27
0.244
0.33 (SOFM)
0.3 (HTF)
0.2 (Fert TALP)
0.175
0.14
0.33
(SOFC1)
0.32 (G1.2)
0.33 (SOFC1)
0.1 (G2.2)
SOF = Synthetic Oviductal Fluid; HTF = Human Tubal Fluid (Quinn et al., 1985); Fert TALP = Modified Tyrode’s
Medium (Gardner et al., 2004); G1.2/G2.2 (Lane et al., 2003). 1Sutton-McDowall et al., 2005; 2Leroy et al., 2004;
3
Lippes et al., 1972; 4Gardner et al., 1996; 5Dickens et al., 1995; 6Carlson et al., 1970 and 7Lopata et al., 1976.
Pre-ovulation: the cumulus oocyte complex
Historically, the carbohydrate metabolism of
the oocyte has been described (Biggers et al., 1967;
Rieger and Loskutoff, 1994; Bavister, 1995; Krisher and
Bavister, 1999; Spindler et al., 2000). However, in the
last decade, the importance of the cumulus cells
supplying the oocyte with nutrients and substrates to
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
achieve developmental competence has emerged
(Dumesic et al., 2015), as a consequence of
understanding the importance of the bi-directional
communication between the oocyte and cumulus
vestment (Eppig, 1991; Albertini et al., 2001; Matzuk et
al., 2002). Thus, characterisation of the metabolic
profile of the COC as a whole is essential in our view.
However, the COC contains two distinct cell types with
409
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
different metabolic profiles: the oocyte predominantly
undergoes oxidative phosphorylation and the cumulus
vestment has a high rate of glycolytic activity
(Thompson et al., 2007). The primary substrate of the
COC is glucose and is metabolised via numerous
pathways to provide energy and substrates for
extracellular
matrix
formation
and
cumulus
mucification, nucleic acid synthesis and plays a major
role as a stress/fuel sensing molecule (reviewed by
Sutton-McDowall et al., 2010). With the progression of
COC maturation, metabolism increases steadily, with
increases in glucose, pyruvate and oxygen consumption
observed (Sutton et al., 2003a).
The environment in which a COC is exposed to
during maturation, both in vivo and in vitro, largely
impacts its developmental competence (Sutton et al.,
2003c; Krisher, 2013; Dumesic et al., 2015). For
example, maternal hyperglycaemia and hyperlipidemia
compromise COC health, embryo development and
pregnancy outcomes (Chang et al., 2005; Leroy et al.,
2008; Robker, 2008; Purcell and Moley, 2011; Van
Hoeck et al., 2011). To date, the technology to measure
the metabolism of oocytes and COCs within the ovarian
follicle does not exist, with measurements performed ex
vivo and usually with some degree of further in vitro
manipulation. This includes physical removal from the
follicle, exposure to culture media, sometimes combined
with hyperstimulation to retrieve adequate numbers of
COCs. This begs the question as to the influence of
even brief exposure to in vitro conditions on the
metabolism of in vivo derived COCs. We have reported
that even a brief exposure (1 h) of immature mouse
COCs to “collection” media containing different
concentrations of glucose can have a dramatic effect on
post-fertilisation embryo development (Frank et al.,
2013). Aspiring to determine the precise differences
between the metabolism of in vivo and in vitro matured
COCs is not possible, as in vivo derived COCs must be
removed to measure their metabolism.
Over the past decade, improvements in IVP
success have largely been attributed to improved IVM
culture systems, by creating environments that more
closely mimic in vivo conditions. Systems that are more
in vivo-like provide clues as to which metabolic
parameters are associated with improved developmental
competence; these are emerging from studies with
media additives that improve COC development. An
example is the addition of exogenous oocyte secreted
factors (OSF), specifically recombinant bone
morphogenetic protein 15 (BMP15) and growth
differentiation factor 9 (GDF9), resulting in improved
developmental competence (Gilchrist and Thompson,
2007). While OSFs promote the distinct cumulus cell
phenotype such as mucification and proliferation
(Buccione et al., 1990; Salustri et al., 1990a, b);
steriodogenesis (Vanderhyden and Macdonald, 1998)
and prevention of cumulus cell apoptosis (Hussein et
al., 2005), OSF also promote cumulus cell metabolism,
410
as both glycolysis and de novo cholesterol biosynthesis
is compromised within cumulus cells of oocytectomised
complexes (OOX, a COC in which the oocyte is
surgically removed). The activity of these pathways can
be restored with the addition of exogenous OSFs
(Sugiura and Eppig, 2005).
The complex nature of COC metabolism
associated with enhanced developmental competence is
well demonstrated by examining the impact of BMP15
and FSH supplementation in vitro. In the absence of
FSH, cattle COCs treated with BMP15 alone consume
less glucose and produce less lactate compared to FSH
treatment alone, this is a predictable consequence of
little cumulus expansion compared to standard IVM
conditions, which utilize FSH. Yet both groups have
similar rates of glycolytic activity (Sutton-McDowall et
al., 2012). Within the oocyte, BMP15 treatment
promotes oxidative phosphorylation and tricarboxylic
acid (TCA) cycle activity (FAD and NAD(P)H,
respectively) and as a consequence, higher levels of
antioxidants (reduced glutathione, GSH) and reactive
oxygen species levels (ROS, H2O2; Sutton-McDowall et
al., 2012, 2015; Sudiman et al., 2014) were detected. In
comparison, FSH stimulates glucose consumption by
cumulus cells, with increasing levels of glucose utilised
via the hexosamine biosynthetic pathway for cumulus
expansion towards the end of IVM (Sutton-McDowall
et al., 2005). Significantly, both these independent
treatments improved developmental competence.
Hence, BMP15 and FSH promote distinct metabolic
pathways within the different compartments of the
COC. When combined, FSH and BMP15 stimulate a
metabolic equilibrium (Sutton-McDowall et al., 2012,
2015), in which the metabolic effect of each was
“masked”, yet this combined treatment yielded the
highest developmental competence (blastocyst rates).
Metabolism pre- and post-compaction
The first stage of oocyte-embryo transition is
oocyte activation following sperm penetration. This
includes the cortical granule reaction and hardening of
the zona pellucida to prevent polyspermy, resumption of
meiosis, pronuclear formation and syngamy. These
events are initiated by cytoplasmic release of small
signalling ions such as calcium and zinc (Wang and
Machaty, 2013; Que et al., 2014), with minimal gene
transcript and energy demand. Zygotes and cleavagestaged embryos rely on the oxidation of carboxylic acids
such as pyruvate and lactate via the TCA cycle and
oxidative phosphorylation within the mitochondria, with
minimal glycolytic activity as the demand for ATP is
low (Fig. 1; Thompson, 2000). Post-compaction, in
morula and blastocyst stage embryos, overall
metabolism increases, with glycolysis becoming the
predominant source of ATP, a pattern seen in mouse
(Houghton et al., 1996), cow (Thompson et al., 1996),
pig (Swain et al., 2001; Sturmey and Leese, 2003) and
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
human (Gott et al., 1990) embryos. In addition, oxygen
consumption, TCA cycle and oxidative phosphorylation
also increase (Thompson, 2000).
Development of improved embryo culture
systems was driven by the inability to overcome the
specific cell-cycle developmental block induced by an
unsupportive culture environment. Early development in
the presence of high levels of glucose and substrates
results in Crabtree-like metabolism (increased
glycolytic activity and depression of oxidative
phosphorylation).
Such
conditions
induce
a
developmental block coinciding with embryonic
genome activation; namely a 2-cell block in mouse
(Lawitts and Biggers, 1991) and at the 8-cell stage in
ruminants (Thompson et al., 1992; Gardner et al., 1997;
Summers and Biggers, 2003). As mentioned previously,
the development of sequential culture systems, adapted
to reflect the metabolic needs of COCs and embryos
(i.e. reduced substrate concentrations in the precompaction period), has resulted in significant
improvements in the developmental outcomes of IVP
embryos, overcoming the developmental blocks.
How to measure metabolism
Metabolism can be measured in two ways,
either direct measurement of metabolites (including
associated proteins, genes or signalling molecules)
within the COC and embryo, or sampling the
surrounding environment, such as in vivo fluids or the
culture media. Sampling of the in vivo environment has
been critical in formulating culture systems based on the
metabolic profiles of COCs and embryos and has
resulted in improved embryo development (Summers
and Biggers, 2003).
Direct measures within the COC, oocyte or embryo
PCR (mRNA), western blots (protein levels
and post-translation modifications), direct enzyme
assays and immunohistochemistry (localisation) have
been used to study the presence and relative activities of
key metabolic enzymes and downstream targets.
However, a large proportion of the initial metabolism
experiments were performed using radiolabelled
substrates. The Hanging Drop assay involves culturing
oocytes or embryos in ~3 μl of culture media containing
cold and hot (radiolabelled) substrates. This drop was
suspended in the lid of a centrifuge tube (or similar
vessel) containing a solution of sodium hydroxide or
sodium bicarbonate (the latter requiring CO2 gassing),
which acts as an isotope “trap” and provides
humidification of the chamber (O'Fallon and Wright,
1986). Depending on which carbon/hydrogen was
labelled, the production of labelled CO2 or H2O
indicated the proportion of the substrate metabolised via
particular pathways. For example, the production of
14
CO2 from [1-14C] glucose measured activity through
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
pentose phosphate pathway (PPP) and TCA cycle.
Likewise, the production of 3H2O from [5-3H] glucose is
indicative of glycolytic activity. A summary diagram of
the metabolism of labelled glucose isotopes is available
in Downs and Utecht (1999).
Widely used in the 1980s-1990s (O'Fallon and
Wright, 1986; Rieger and Guay, 1988; Downs and
Utecht, 1999), the advantages of the Hanging Drop
method included the radiolabelled products amplifying
the metabolic signal, resulting in high sensitivity and the
ability to measure metabolic pathway activity in single
oocytes and embryos (Bavister, 1987). Classed as noninvasive, embryo transfers could be performed at the
completion of the assay period (O'Fallon and Wright,
1986). However, this assay could not be used in
conjunction with embryo transfer in human embryos
due to the use of radiolabelled substrates. Furthermore,
the availability of commercially available assays that
allows absolute concentrations of substrates to be
determined has increased. Examples of commercially
available kits include ADP/ATP kits (Sutton-McDowall
et al., 2012; Zeng et al., 2013; Richani et al., 2014) or
clinical chemical analysers for pyruvate, lactate and
glucose.
The influence of metabolism on development
can be studied using inhibitors and/or stimulators of
specific enzymes within metabolic pathways. Oocytes
and embryos are cultured in the presence of the
antagonists/agonists and outputs such as nuclear
maturation and developmental stage would then be
assessed (Downs, 1997; Downs and Mastropolo, 1997;
Downs et al., 1998; Downs and Utecht, 1999; SuttonMcDowall et al., 2006). In combination with other
measurements of metabolism such as substrate turnover,
the use of antagonists and agonists remains highly
valuable in determining the impact of a metabolic
pathway on oocyte and/or embryo competence.
More recently, the development of a variety of
effective fluorescent probes that react with specific
enzymes or substrate, combined with improved
accessibility to confocal microscopy technology has
improved the measurement of the metabolism at the
single oocyte and embryo level as it has the capacity to
combine information on quantification and localisation
of activity. Unlike traditional labelling, such as
immunohistochemistry, where cells need to undergo
extensive processing, such as fixation and
permeabilisation, a large proportion of these newer
probes are designed for use in live cells. For example,
glucose uptake into a COC can be measured using 6-(N(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-6deoxyglucose (6-NBDG), a fluorescent glucose
analogue that is non hydrolyzable (Sutton-McDowall et
al., 2010; Wang et al., 2012a, b), and this method of
studying glucose uptake complements measures of
expression of glucose transporter genes (Wang et al.,
2012a, b).
Improved and increased accessibility to
411
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
commercially available probes has been particularly
advantageous to the study of mitochondria. Since
mitochondrial health and functionality is dependent on
multiple factors such as density, localisation and
distribution, maturity and activity (Babayev and Seli,
2015), the following paragraphs will use mitochondrial
labelling as an example of how probes target different
characteristics.
The most commonly used mitochondrial
probes are JC-1 and Mitotracker probes. JC-1 (5,5',6,6'tetrachloro-1,1',3,3'tetraethylbenzimidazolylcarbocyanine iodide) is a dual
emission, ratio-metric probe that has been utilized to
measurement changes in mitochondrial membrane
potential (ΔΨm) in live mouse and human oocytes (Diaz
et al., 1999; Wilding et al., 2001; Van Blerkom et al.,
2002, 2003; Zeng et al., 2013). When ΔΨm is low, JC-1
exists as a monomer (green emission) and is converted
to J-aggregates/dimers (red emission) with high ΔΨm.
Hence, the ratio of red to green fluorescence indicates
changes in ΔΨm independent of mitochondrial size,
shape and density. However, JC-1 has disadvantages, as
it is very sensitive to concentration; with the use of too
high JC-1 concentrations leading to false positives, is
highly sensitive to other factors such as H2O2, requires a
long incubation time and has poor cell retention (Perry
et al., 2011). While JC-1 works well in rodent oocytes
and embryos, in our experience JC-1 has poor cellular
permeability when incubated with cattle oocytes and
embryos, requiring cell permeabilisation or removal of
the zona pellucida; both processes may harm an oocyte
and embryo, and therefore not favourable considering
the probe is assessing cell function.
Alternatives to JC-1 are the Mitotracker range
of probes: mildly thiol-reactive chloromethyl moieties
that are lipophilic cations, hence are highly cell
permeable and only fluoresce within cells. Furthermore,
they are more robust than JC-1, with higher
photostability, require less reaction time, have higher
cell retainability and less cross-reactivity with other
factors (Perry et al., 2011). There are two main forms of
Mitotracker probes; carboryanine or rosamine based.
The fluorescence of carboryanine base probes, such as
Mitotracker Green FM (MTG) are independent of ΔΨm,
hence indicators of total mitochondrial mass in
combination with localization, particularly useful in
studies comparing mitochondrial biosynthesis in
immature vs. mature oocytes (Stojkovic et al., 2001;
Sun et al., 2001; Sturmey et al., 2006; Gendelman and
Roth, 2012). In comparison, rosamine based probes,
such as Mitotracker CMXRos, (MTR) are oxidized
within cells and sequestered within the mitochondria,
hence indicators of ΔΨm and activity (Castaneda et al.,
2013; Viet Linh et al., 2013; Niu et al., 2015; Sanchez
et al., 2015; Sutton-McDowall et al., 2015). In a similar
concept to JC-1, cells can be co-labelled with MTR and
MTG to determine a ratio of active to total mitochondria
(Pendergrass et al., 2004), although to our knowledge,
412
such a comparison has not been performed in oocytes or
embryos.
With advancements in probe design,
microscopy and imaging technology, image analyses
has also evolved to measure different pixel attributes,
such as distribution, co-localization and patterning, in
addition to pixel intensity. This can improve the quality
of information about the role of mitochondria under
different states of oocyte and embryo health. Ultrasound
sonography, dermatology and cancer research are fields
that routinely use advanced imaging matrices to assess
variations in patterns of pixel characteristics such as
wrinkles, smoothness, uniformity and entropy
(Castellano et al., 2004; Alvarenga et al., 2007; Mittra
and Parekh, 2011) of images. In comparison, image
analysis within the pre-implantation research field is
largely limited to measurements of fluorescence
intensity or visual assessment. We have recently utilized
texture analyses (Haralick et al., 1973; Murata et al.,
2001; Cabrera, 2006) to assess the influence of exposing
cattle COCs to FSH and BMP15 on the distribution of
MTR, monochlorobimane (MCB; indicative of reduced
glutathione) and peroxyfluor 1 (PF1; measures levels of
H2O2, a derivative of reactive oxygen species; SuttonMcDowall et al., 2015). In addition to pixel intensity,
textural analyses demonstrated an association with
homogeneous localization of fluorescence with
improved
developmental
competence
(SuttonMcDowall et al., 2015). As technology improves, the
mechanisms through which outputs are measured will
continue to evolve.
While fluorescent probe are of value to the
study of metabolism, label-free and non-toxic methods
for characterising metabolism and viability would be
preferable, in particular as a potential diagnostic of
oocyte and embryo health. Electron donors
NADPH/NADH (NAD(P)H) and the electron acceptor
FAD are endogenous fluorophores with different
spectral properties and therefore can be measured
simultaneously by confocal microscopy. NADH has
both cytoplasmic and mitochondrial localisation,
whereas FAD is exclusively localised to the
mitochondria (Table 2). FAD and NAD(P)H are critical
for energy homeostasis, hence measurement of levels
indicates the redox state of cells (FAD: NAD(P)H;
Skala and Ramanujam, 2010). Measurement of intra
cellular autofluorescence has not been widely exploited
for investigations into cellular metabolism of embryos.
However, Dumollard et al., 2007a, b) utilised
autofluorescence as a method for label-free localisation
of mitochondria (Dumollard et al., 2007a) and to study
the influence of energy substrates on redox state over
time (Dumollard et al., 2007b). Furthermore,
autofluorescence measurements have demonstrated
changes in redox ratios in COCs following IVM in the
presence of OSF (Sutton-McDowall et al., 2012, 2015;
Sugimura et al., 2014) and EGF-like peptides (Richani
et al., 2014).
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
Table 2. Parameters of autofluorescence molecules involved in metabolism.
NADH
Electron
Donor
Localisation
Cytoplasm
Mitochondria
NADPH
FAD
Donor
Accepter
Cytoplasm
Mitochondria
Pathways
Glycolysis
TCA cycle
Oxidative Phosphorylation
PPP
Oxidative Phosphorylation
Sampling of the culture media
Standard techniques for measuring metabolites
include mass spectrometry/chromatography and clinical
chemical analysers (Sutton-McDowall et al., 2012,
2014). Leese and colleagues devised fluorometric
assays for measuring nano and pico litres of samples
based on the oxidation and/or reduction of
autofluorescence signalling molecules such as FAD and
NAD(P)H (Leese and Bronk, 1972). Indeed, many of
these assays are still used due to their high sensitivity
and the ability to measure the metabolite turnover of a
single COC and embryo.
Metabolomics is the newest member of the
“omics” family and unlike other metabolic assays,
brings a more holistic approach to profiles, as it allows
not only measurement of substrate turnover but also
changes in pathway activity and downstream targets
(Krisher et al., 2015). Metabolomics combines two
technologies to separate (gas chromatography or high
performance liquid chromatography) and detect (mass
spectrometry, nuclear magnetic resonance or Raman
spectrometry) larger numbers of metabolites within
spent culture media compared to fluorometric assays
and other analytical methods. Both quantitative or
qualitative measurements can be performed with
quantitative measures requiring the generation of
standard curves, which limits the number of substrates
that can be measured (Thompson et al., 2014).
Successful application of some metabolomics platforms
for spent media analysis to measure embryo quality
were initially favourable and indeed still pursued
(Krisher et al., 2015), but has since been abandoned for
use in human IVF, as results were inconsistent and
dependent on media formulations.
The future for metabolic measurement of oocytes
and embryos
A massive knowledge gap remains in
characterising the metabolome of COCs and embryos in
vivo as the ability to measure this in situ is essentially
non-existent. There is a need to create new technologies
that allow for in vivo measurement of biochemical
reactions, given that even short exposures to in vitro
conditions can alter COC and embryo metabolism. The
development of remote sensing diagnostics, such as
micro optical fibres and nano-particles are options for
remote sensing with minimal invasion. An ideal
candidate is the adaptions of multiphoton endoscopes to
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Excitation (nm)
350
Emission (nm)
460
350
450
460
535
micro-optical fibres to allow for in vivo measurement of
autofluorescence, hence redox state of COCs and
embryos (Helmchen, 2002).
Even in vitro, the metabolic requirements of
COCs are dynamic, with high levels of plasticity, where
as most measurements are taken at a single time point.
Furthermore, numerous metabolic pathways are in play
and differential activity can result in numerous
downstream consequences. For this reason, the use of
single measurements of single metabolic outputs is not
sufficient. Platforms that allow multi sampling of
different aspects of metabolism are critical for
advancing our knowledge of COC maturation. This
could be achieved using label-free technologies and
non-toxic, reversible probes, allowing for repeated
measurements and changes in metabolism, crucial for
dynamic periods in development such as oocyte
maturation, fertilisation and embryonic genome
activation. Essentially measuring more in less. A longterm goal could involve the development of sensing
probes and systems that could be integrated into
incubators, allowing the constant monitoring of changes
in metabolism and thereby predict oocyte and embryo
health and quality.
References
Albertini DF, Combelles CM, Benecchi E,
Carabatsos MJ. 2001. Cellular basis for paracrine
regulation
of
ovarian
follicle
development.
Reproduction, 121:647-653.
Alvarenga AV, Pereira WC, Infantosi AF, Azevedo
CM. 2007. Complexity curve and grey level cooccurrence matrix in the texture evaluation of breast
tumor on ultrasound images. Med Phys, 34:379-387.
Babayev E, Seli E. 2015. Oocyte mitochondrial
function and reproduction. Curr Opin Obstet Gynecol,
27:175-181.
Bavister BD. 1987. The Mammalian Preimplantation
Embryo: Regulation of Growth and Differentiation In
Vitro. New Yok, NY: Plenum Press.
Bavister BD. 1995. Culture of preimplantation
embryos: facts and artifacts. Hum Reprod Update, 1:91148.
Biggers JD, Whittingham DG, Donahue RP. 1967.
The pattern of energy metabolism in the mouse oocyte
and zygote. Zoology, 58: 560-567.
Buccione R, Vanderhyden BC, Caron PJ, Eppig JJ.
1990. FSH-induced expansion of the mouse cumulus
oophorus in vitro is dependent upon a specific factor(s)
413
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
secreted by the oocyte. Dev Biol, 138:16-25.
Cabrera J. 2006. Texture analyzer. July 7, 2006.
Available on: http://rsbweb.nih.gov/ij/plugins/texture.html.
Carlson D, Black DL, Howe GR. 1970. Oviduct
secretion in the cow. J Reprod Fertil, 22:549-552.
Castaneda CA, Kaye P, Pantaleon M, Phillips N,
Norman S, Fry R, D'Occhio MJ. 2013. Lipid content,
active mitochondria and brilliant cresyl blue staining in
bovine oocytes. Theriogenology, 79:417-422.
Castellano G, Bonilha L, Li LM, Cendes F. 2004.
Texture analysis of medical images. Clin Radiol,
59:1061-1069.
Chang AS, Dale AN, Moley KH. 2005. Maternal
diabetes adversely affects preovulatory oocyte
maturation, development, and granulosa cell apoptosis.
Endocrinology, 146:2445-2453.
Cohen J, Rieger D, Wiemer K. 2008. A single
medium for culture of the human embryo from zygote
to blastocyst. Reprod Biomed Online, 17:S-19.
Diaz G, Setzu MD, Zucca A, Isola R, Diana A,
Murru R, Sogos V, Gremo F. 1999. Subcellular
heterogeneity of mitochondrial membrane potential:
relationship with organelle distribution and intercellular
contacts in normal, hypoxic and apoptotic cells. J Cell
Sci, 112( pt.7):1077-1084.
Dickens CJ, Maguiness SD, Comer MT, Palmer A,
Rutherford AJ, Leese HJ. 1995. Human tubal fluid:
formation and composition during vascular perfusion of
the fallopian tube. Hum Reprod, 10:505-508.
Downs SM. 1997. Involvement of purine nucleotide
synthetic pathways in gonadotropin- induced meiotic
maturation in mouse cumulus cell-enclosed oocytes.
Mol Reprod Dev, 46:155-167.
Downs SM, Mastropolo AM. 1997. Culture conditions
affect meiotic regulation in cumulus cell-enclosed
mouse oocytes. Mol Reprod Dev, 46:551-566.
Downs SM, Humpherson PG, Leese HJ. 1998.
Meiotic induction in cumulus cell-enclosed mouse
oocytes: involvement of the pentose phosphate pathway.
Biol Reprod, 58:1084-1094.
Downs SM, Utecht AM. 1999. Metabolism of
radiolabeled glucose by mouse oocytes and oocytecumulus cell complexes. Biol Reprod, 60:1446-1452.
Dumesic DA, Meldrum DR, Katz-Jaffe MG, Krisher
RL, Schoolcraft WB. 2015. Oocyte environment:
follicular fluid and cumulus cells are critical for oocyte
health. Fertil Steril, 103:303-316.
Dumollard R, Duchen M, Carroll J. 2007a. The role
of mitochondrial function in the oocyte and embryo.
Curr Top Dev Biol, 77:21-49.
Dumollard R, Ward Z, Carroll J, Duchen MR.
2007b. Regulation of redox metabolism in the mouse
oocyte and embryo. Development, 134:455-465.
Dunning K, Russell DL, Robker R. 2014. Lipids and
oocyte developmental competence: the role of fatty
acids and B-oxidation. Reproduction, 148:R15-27.
Edwards RG. 1965. Maturation in vitro of mouse,
sheep, cow, pig, rhesus monkey and human ovarian
414
oocytes. Nature, 208:349-351.
Eppig JJ. 1991. Intercommunication between
mammalian oocytes and companion somatic cells.
Bioessays, 13:569-574.
Fischer B, Bavister BD. 1993. Oxygen tension in the
oviduct and uterus of rhesus monkeys, hamsters and
rabbits. J Reprod Fertil, 99:673-679.
Frank LA, Sutton-McDowall ML, Russell DL, Wang
X, Feil DK, Gilchrist RB, Thompson JG. 2013. Effect
of varying glucose and glucosamine concentration in
vitro on mouse oocyte maturation and developmental
competence. Reprod Fertil Dev, 25:1095-104.
Gandhi AP, Lane M, Gardner DK, Krisher RL.
2000. A single medium supports development of bovine
embryos throughout maturation, fertilization and
culture. Hum Reprod, 15:395-401.
Gardner DK, Lane M, Calderon I, Leeton J. 1996.
Environment of the preimplantation human embryo in
vivo: metabolite analysis of oviduct and uterine fluids
and metabolism of cumulus cells. Fertil Steril, 65:349353.
Gardner DK, Lane MW, Lane M. 1997. Bovine
blastocyst cell number is increased by culture with
EDTA for the first 72 hours of development from the
zygote. Theriogenology, 47:278. (abstract).
Gardner DK, Lane M, Watson AJ. 2004. A
Laboratory Guide to the Mammalian Embryo. New
York, NY: Oxford University Press.
Gendelman M, Roth Z. 2012. Incorporation of
coenzyme Q10 into bovine oocytes improves
mitochondrial features and alleviates the effects of
summer thermal stress on developmental competence.
Biol Reprod, 87:118. doi: 10.1095/biolreprod.112.101881.
Gilchrist RB, Thompson JG. 2007. Oocyte
maturation: emerging concepts and technologies to
improve
developmental
potential
in
vitro.
Theriogenology, 67:6-15.
Gott AL, Hardy K, Winston RM, Leese HJ. 1990.
Non-invasive measurement of pyruvate and glucose
uptake and lactate production by single human
preimplantation embryos. Hum Reprod, 5:104-108.
Haralick RM, Shanmuga K, Dinstein I. 1973.
Textural features for image classification. IEEE Trans
Syst Man Cyb, Smc3:610-621.
Helmchen F. 2002. Miniaturization of fluorescence
microscopes using fibre optics. Exp Physiol, 87:737745.
Houghton FD, Thompson JG, Kennedy CJ, Leese
HJ. 1996. Oxygen consumption and energy metabolism
of the early mouse embryo. Mol Reprod Dev, 44:476485.
Hussein TS, Froiland DA, Amato F, Thompson JG,
Gilchrist RB. 2005. Oocytes prevent cumulus cell
apoptosis by maintaining a morphogenic paracrine
gradient of bone morphogenetic proteins. J Cell Sci,
118:5257-5268.
Krisher R. 2013. In vivo and in vitro environmental
effects on mammalian oocyte quality. Ann Rev Anim
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
Biosci, 1:393-417.
Krisher RL, Bavister BD. 1999. Enhanced glycolysis
after maturation of bovine oocytes in vitro is associated
with increased developmental competence. Mol Reprod
Dev, 53:19-26.
Krisher RL, Heuberger AL, Paczkowski M, Stevens
J, Pospisil C, Prather RS, Sturmey RG, Herrick JR,
Schoolcraft, WB. 2015. Applying metabolomic
analyses to the practice of embryology: physiology,
development and assisted reproductive technology.
Reprod Fertil Dev. doi: 10.1071/RD14359.
Lane M, Gardner DK, Hasler M, Hasler JF. 2003.
Use of G1.2/G2.2 media for commercial bovine embryo
culture: equivalent development and pregnancy rates
compared to co-culture. Theriogenology, 60:407-419.
Lane M, Gardner DK. 2007. Embryo culture medium:
which is the best? Best Pract Res Clin Obstet Gynaecol,
21:83-100.
Lawitts JA, Biggers JD. 1991. Overcoming the 2-cell
block by modifying standard components in a mouse
embryo culture medium. Biol Reprod, 45:245-251.
Leese HJ, Bronk JR. 1972. Automated fluorometric
analysis of micromolar quantities of ATP, glucose, and
lactic acid. Anal Biochem, 45:211-221.
Leese HJ, Baumann CG, Brison DR, McEvoy TG,
Sturmey RG. 2008. Metabolism of the viable
mammalian embryo: quietness revisited. Mol Hum
Reprod, 14:667-672.
Leese HJ. 2012. Metabolism of the preimplantation
embryo: 40 years on. Reproduction, 143:417-427.
Leroy JL, Vanholder T, Delanghe JR, Opsomer G,
Van Soom A, Bols PE, de Kruif A. 2004. Metabolite
and ionic composition of follicular fluid from differentsized follicles and their relationship to serum
concentrations in dairy cows. Anim Reprod Sci, 80:201211.
Leroy JL, Van Soom A, Opsomer G, Bols PE. 2008.
The consequences of metabolic changes in highyielding dairy cows on oocyte and embryo quality.
Animal, 2:1120-1127.
Lippes J, Enders RG, Pragay DA, Bartholomew
WR. 1972. The collection and analysis of human
fallopian tubal fluid. Contraception, 5:85-103.
Lopata A, Patullo MJ, Chang A, James B. 1976. A
method for collecting motile spermatozoa from human
semen. Fertil Steril, 27:677-684.
Maas DH, Storey BT, Mastroianni L Jr. 1976.
Oxygen tension in the oviduct of the rhesus monkey
(Macaca mulatta). Fertil Steril, 27:1312-1317.
Matzuk MM, Burns KH, Viveiros MM, Eppig JJ.
2002. Intercellular communication in the mammalian
ovary: oocytes carry the conversation. Science,
296:2178-2180.
Mittra AK, Parekh R. 2011. Automated detection of
skin diseases using texture features. Int J Eng Sci
Technol, 3:4801-4808.
Murata S, Herman P, Lakowicz JR. 2001. Texture
analysis of fluorescence lifetime images of AT- and
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
GC-rich regions in nuclei. J Histochem Cytochem,
49:1443-1451.
Niu Y, Wang C, Xiong Q, Yang X, Chi D, Li P, Liu
H, Li J, Huang R. 2015. Distribution and content of
lipid
droplets
and
mitochondria
in
pig
parthenogenetically activated embryos after delipation.
Theriogenology, 83:131-138.
O'Fallon JV, Wright RW Jr. 1986. Quantitative
determination of the pentose phosphate pathway in
preimplantation mouse embryos. Biol Reprod, 34:58-64.
Paternot G, Debrock S, D'Hooghe TM, Spiessens C.
2010. Early embryo development in a sequential versus
single medium: a randomized study. Reprod Biol
Endocrinol, 8:83,7 pp.
Pendergrass W, Wolf N, Poot M. 2004. Efficacy of
mitotracker green and CMXrosamine to measure
changes in mitochondrial membrane potentials in living
cells and tissues. Cytometry A, 61:162-169.
Perry SW, Norman JP, Barbieri J, Brown EB,
Gelbard HA. 2011. Mitochondrial membrane potential
probes and the proton gradient: a practical usage guide.
Biotechniques, 50:98-115.
Purcell SH, Moley KH. 2011. The impact of obesity on
egg quality. J Assist Reprod Genet, 28:517-524.
Que EL, Bleher R, Duncan FE, Kong BY, Gleber
SC, Vogt S, Chen S, Garwin SA, Bayer AR, Dravid
VP, Woodruff TK, O'Halloran TV. 2014.
Quantitative mapping of zinc fluxes in the mammalian
egg reveals the origin of fertilization-induced zinc
sparks. Nat Chem, 7:130-139.
Quinn P, Kerin JF, Warnes GM. 1985. Improved
pregnancy rate in human in vitro fertilization with the
use of a medium based on the composition of human
tubal fluid. Fertil Steril, 44:493-498.
Restall BJ, Wales RG. 1966. The fallopian tube of the
sheep. 3. The chemical composition of the fluid from
the fallopian tube. Aust J Biol Sci, 19:687-698.
Richani D, Sutton-McDowall ML, Frank LA,
Gilchrist RB, Thompson JG. 2014. Effect of
epidermal growth factor-like peptides on the
metabolism of in vitro- matured mouse oocytes and
cumulus
cells.
Biol
Reprod,
90:49.
doi:
10.1095/biolreprod.113.115311.
Rieger D, Guay P. 1988. Measurement of the
metabolism of energy substrates in individual bovine
blastocysts. J Reprod Fertil, 83:585-591.
Rieger D, Loskutoff NM. 1994. Changes in the
metabolism of glucose, pyruvate, glutamine and glycine
during maturation of cattle oocytes in vitro. J Reprod
Fertil, 100:257-262.
Robker RL. 2008. Evidence that obesity alters the
quality of oocytes and embryos. Pathophysiology,
15:115-121.
Salustri A, Ulisse S, Yanagishita M, Hascall VC.
1990a. Hyaluronic acid synthesis by mural granulosa
cells and cumulus cells in vitro is selectively stimulated
by a factor produced by oocytes and by transforming
growth factor-beta. J Biol Chem, 265:19517-19523.
415
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
Salustri A, Yanagishita M, Hascall VC. 1990b.
Mouse oocytes regulate hyaluronic acid synthesis and
mucification by FSH-stimulated cumulus cells. Dev
Biol, 138:26-32.
Sanchez F, Romero S, De Vos M, Verheyen G, Smitz
J. 2015. Human cumulus-enclosed germinal vesicle
oocytes from early antral follicles reveal heterogeneous
cellular and molecular features associated with in vitro
maturation capacity. Hum Reprod, 30:1396-409.
Skala M, Ramanujam N. 2010. Multiphoton redox
ratio imaging for metabolic monitoring in vivo. Methods
Mol Biol, 594:155-162.
Spindler RE, Pukazhenthi BS, Wildt DE. 2000. Oocyte
metabolism predicts the development of cat embryos to
blastocyst in vitro. Mol Reprod Dev, 56:163-171.
Stojkovic M, Machado SA, Stojkovic P,
Zakhartchenko V, Hutzler P, Goncalves PB, Wolf E.
2001. Mitochondrial distribution and adenosine
triphosphate content of bovine oocytes before and after
in vitro maturation: correlation with morphological
criteria and developmental capacity after in vitro
fertilization and culture. Biol Reprod, 64:904-909.
Sturmey RG, Leese HJ. 2003. Energy metabolism in
pig oocytes and early embryos. Reproduction, 126:197204.
Sturmey RG, O'Toole PJ, Leese HJ. 2006.
Fluorescence resonance energy transfer analysis of
mitochondrial:lipid association in the porcine oocyte.
Reproduction, 132:829-837.
Sturmey RG, Reis A, Leese HJ, McEvoy TG. 2009.
Role of fatty acids in energy provision during oocyte
maturation and early embryo development. Reprod
Domest Anim, 44(suppl.3):50-58.
Sudiman J, Sutton-McDowall ML, Ritter LJ, White
MA, Mottershead DG, Thompson JG, Gilchrist RB.
2014. Bone morphogenetic protein 15 in the pro-mature
complex form enhances bovine oocyte developmental
competence. PLoS One, 9:e103563.
Sugimura S, Ritter, LJ, Sutton-McDowall ML,
Mottershead DG, Thompson JG, Gilchrist RB. 2014.
Amphiregulin co-operates with bone morphogenetic
protein 15 to increase bovine oocyte developmental
competence: effects on gap junction-mediated
metabolite supply. Mol Hum Reprod, 20:499-513.
Sugiura K, Eppig JJ. 2005. Society for Reproductive
Biology Founders' Lecture 2005. Control of metabolic
cooperativity between oocytes and their companion
granulosa cells by mouse oocytes. Reprod Fertil Dev,
17:667-674.
Summers MC, Biggers JD. 2003. Chemically defined
media and the culture of mammalian preimplantation
embryos: historical perspective and current issues. Hum
Reprod Update, 9:557-582.
Sun QY, Wu GM, Lai L, Park KW, Cabot R,
Cheong HT, Day BN, Prather RS, Schatten H. 2001.
Translocation of active mitochondria during pig oocyte
maturation, fertilization and early embryo development
in vitro. Reproduction, 122:155-163.
416
Sutton ML, Cetica PD, Beconi MT, Kind KL,
Gilchrist RB, Thompson JG. 2003a. Influence of
oocyte-secreted factors and culture duration on the
metabolic activity of bovine cumulus cell complexes.
Reproduction, 126:27-34.
Sutton ML, Cetica PD, Gilchrist RB, Thompson JG.
2003b. The metabolic profiles of bovine cumulusoocyte complexes: effects of oocyte-secreted factors and
stimulation of cumulus expansion. Theriogenology,
59:500. (abstract).
Sutton ML, Gilchrist RB, Thompson JG. 2003c.
Effects of in-vivo and in-vitro environments on the
metabolism of the cumulus-oocyte complex and its
influence on oocyte developmental capacity. Hum
Reprod Update, 9:35-48.
Sutton-McDowall ML, Gilchrist RB, Thompson JG.
2005. Effect of hexoses and gonadotrophin
supplementation on bovine oocyte nuclear maturation
during in vitro maturation in a synthetic follicle fluid
medium. Reprod Fertil Dev, 17:407-415.
Sutton-McDowall ML, Mitchell M, Cetica P, Dalvit
G, Pantaleon M, Lane M, Gilchrist RB, Thompson
JG. 2006. Glucosamine supplementation during in vitro
maturation inhibits subsequent embryo development:
possible role of the hexosamine pathway as a regulator
of developmental competence. Biol Reprod, 74:881888.
Sutton-McDowall M, Gilchrist R, Thompson J. 2010.
The pivotal role of glucose metabolism in determining
oocyte developmental competence. Reproduction,
139:685-695.
Sutton-McDowall ML, Mottershead DG, Gardner
DK, Gilchrist RB, Thompson JG. 2012. Metabolic
differences in bovine cumulus-oocyte complexes
matured in vitro in the presence or absence of folliclestimulating hormone and bone morphogenetic protein
15. Biol Reprod, 87:87, 81-88.
Sutton-McDowall ML, Yelland R, Macmillan KL,
Robker RL, Thompson JG. 2014. A study relating the
composition of follicular fluid and blood plasma from
individual Holstein dairy cows to the in vitro
developmental competence of pooled abattoir-derived
oocytes. Theriogenology, 82:95-103
Sutton-McDowall ML, Purdey M, Brown HM, Abell
AD, Mottershead DG, Cetica PD, Dalvit GC, Goldys
EM, Gilchrist RB, Gardner DK, Thompson JG.
2015. Redox and anti-oxidant state within cattle oocytes
following in vitro maturation with bone morphogenetic
protein 15 and follicle stimulating hormone. Mol
Reprod Dev, 82:281-294.
Swain JE, Bormann CL, Krisher RL. 2001.
Development and viability of in vitro derived porcine
blastocysts cultured in NCSU23 and G1.2/G2.2
sequential medium. Theriogenology, 56:459-469.
Tervit HR, Whittingham DG, Rowson LE. 1972.
Successful culture in vitro of sheep and cattle ova. J
Reprod Fertil, 30:493-497.
Thompson JG, Simpson AC, Pugh PA, Tervit HR.
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
Sutton-McDowall and Thompson. Measuring metabolism in pre-implantation embryos.
1992. Requirement for glucose during in vitro culture of
sheep preimplantation embryos. Mol Reprod Dev,
31:253-257
Thompson JG, Partridge RJ, Houghton FD, CoxCI,
Leese HJ. 1996. Oxygen uptake and carbohydrate
metabolism by in vitro derived bovine embryos. J
Reprod Fertil, 106:299-306.
Thompson JG. 2000. In vitro culture and embryo
metabolism of cattle and sheep embryos - a decade of
achievement. Anim Reprod Sci, 60-61:263-275.
Thompson JG, Lane M, Gilchrist RB. 2007.
Metabolism of the bovine cumulus-oocyte complex and
influence on subsequent developmental competence.
Soc Reprod Fertil Suppl, 64:179-190.
Thompson JG, Gilchrist RB, Sutton-McDowall ML.
2014. Metabolism of the bovine cumulus oocyte
complex revisited. In: Juengel JL, Miyamoto A, Price C,
Reynolds LP, Smith MF, Webb R (Ed.). Reproduction
in Domestic Ruminants VIII. London, UK: Society for
Reproduction and Fertility. vol. 1, pp. 311-326.
Van Blerkom J, Davis P, Mathwig V, Alexander S.
2002. Domains of high-polarized and low-polarized
mitochondria may occur in mouse and human oocytes
and early embryos. Hum Reprod, 17:393-406.
Van Blerkom J, Davis P, Alexander S. 2003. Inner
mitochondrial membrane potential (DeltaPsim),
cytoplasmic ATP content and free Ca2+ levels in
metaphase II mouse oocytes. Hum Reprod, 18:24292440.
Van Hoeck V, Sturmey RG, Bermejo-Alvarez P,
Rizos D, Gutierrez-Adan A, Leese HJ, Bols PE,
Leroy JL. 2011. Elevated non-esterified fatty acid
concentrations during bovine oocyte maturation
compromise early embryo physiology. PloS One,
6:e23183.
Vanderhyden BC, Macdonald EA. 1998. Mouse
Anim. Reprod., v.12, n.3, p.408-417, Jul./Sept. 2015
oocytes regulate granulosa cell steroidogenesis
throughout follicular development. Biol Reprod,
59:1296-1301.
Viet Linh N, Kikuchi K, Nakai M, Tanihara F,
Noguchi J, Kaneko H, Dang-Nguyen TQ, Men NT,
Van Hanh N, Somfai T, Nguyen BX, Nagai T,
Manabe N. 2013. Fertilization ability of porcine
oocytes reconstructed from ooplasmic fragments
produced and characterized after serial centrifugations.
J Reprod Dev, 59:549-556.
Wale PL, Gardner DK. 2012. Oxygen regulates amino
acid turnover and carbohydrate uptake during the
preimplantation period of mouse embryo development.
Biol Reprod, 87:24, 21-28.
Wang C, Machaty Z. 2013. Calcium influx in
mammalian eggs. Reproduction, 145:R97-R105.
Wang Q, Chi MM, Moley KH. 2012a. Live imaging
reveals the link between decreased glucose uptake in
ovarian cumulus cells and impaired oocyte quality in
female diabetic mice. Endocrinology, 153:1984-1989.
Wang Q, Chi MM, Schedl T, Moley KH. 2012b. An
intercellular pathway for glucose transport into mouse
oocytes. Am J Physiol Endocrinol Metab, 302:E15111518.
Wilding M, Dale B, Marino M, di Matteo L, Alviggi
C, Pisaturo ML, Lombardi L, De Placido G. 2001.
Mitochondrial aggregation patterns and activity in
human oocytes and preimplantation embryos. Hum
Reprod, 16:909-917.
Zeng HT, Ren Z, Guzman L, Wang X, SuttonMcDowall ML, Ritter LJ, De Vos M, Smitz J,
Thompson JG, Gilchrist RB. 2013. Heparin and
cAMP modulators interact during pre-in vitro
maturation to affect mouse and human oocyte meiosis
and developmental competence. Hum Reprod, 28:15361545.
417